Senior Research Scientist, AWS Incident Tooling
7 days ago
You'll join a diverse team of software, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security and availability. You'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
AWS Incident Response is at the heart of the high availability of Amazon Web Services. We make customer impacting events shorter and less frequent by driving large scale event and incident response. Our automated tooling quickly identifies the cause of an issue and helps mitigate its impact, and much of our engineer time is spent on projects to improve the tooling and automation. We also provide manual incident management for AWS and other Amazon groups, directing the resolution of an issue with service teams, and diving deep into those events to drive improvements to the tooling. It's an exciting time to join our team as we are growing and expanding our offerings.
Key job responsibilities
You will own the organisation strategy relative to the usage of ML, GenAI and propose the best technology to advance our ability to better detect, faster root cause ,and correlate to prior incidents to shorten customer facing AWS incidents. Your work will enable us to identify gaps in our current strategy, learnings from past incidents. You will contribute to shortening incident response through deep analysis and introduction of new technology.
About the team
AWS Infrastructure Services (AIS)
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we're looking for talented people who want to help.
You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
BASIC QUALIFICATIONS
- Masters degree (or European advanced degree equivalent) or PhD in Computer Science, or related technical, math, economics, or scientific field- Several years of relevant experience in developing large scale machine learning or deep learning models and/or systems in a production environment
- Experience in using Python, R or Matlab or other statistical/machine learning software language
- Several year experience specifically with deep learning (e.g., CNN, RNN, LSTM, etc.)
- Experience hiring or mentoring more junior colleagues
PREFERRED QUALIFICATIONS
- PhD degree in computer science, engineering, mathematics, economics, or related technical/scientific field- Hands on experience building models with deep learning frameworks like PyTorch, or similar
- Experience with machine learning, time series, NLP and CV solutions
- Proven communication skills, presentation skills, and attention to detail
- Comfortable working in a fast paced, highly collaborative, dynamic work environment
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
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